A new way of mapping

Artisense develops a 3D-vision technology for autonomous cars and robots to navigate effectively.

Founded in 2015, Artisense, a spin-off of Technical University of Munich, develops computer vision and deep learning algorithms that can optimise the mapping and localisation of autonomous robots. Based in Palo Alto (California), the start-up with 40 employees also has offices in Munich and Tokyo. It has mapped areas in Munich, San Francisco and Tokyo and is currently recording all of Berlin.

Technologist: How can Artisense contribute to the development of tomorrow’s mobility?

Christoph Bonik: All the new autonomous agents such as drones, robots or cars need perfect vision and maps to interact with and navigate in dynamic environments. Artisense provides a real-time 3D reconstruction (or mapping) and localization engine. Instead of relying on GPS for positioning – often inaccurate and not available in all locations – and expensive sensor systems for mapping, we use computer vision and AI to turn cameras and off-the-shelf sensors into powerful 3D mapping systems for every environment. Our retro-fit sensor can easily be installed in any vehicle or fleet to collect data for a dynamic, globally consistent, and scalable 3D map.

T.: Can we say that some services such as Google Maps are your main competitors?

C.B.: No, these services are not our direct competitors because they are only built for human use. Such tools in 2D only provide static maps that are often inaccurate, out of date and not compatible with autonomous systems. Our 3D maps are purpose built for localization and optimized for machine consumption. For vehicles to reliably manoeuvre complex traffic situations, they require centimetre accurate understanding of their environment and their own location. Our data feeds the planning and control software that enable robots to perform intelligent long-term scene interactions. Also, being able to locate without GPS, we enable operation in GPS denied areas, such as urban centres or tunnels.

T.: When can we expect first concrete results?

C.B.: We have already deployed sensors and maps with early customers. You can expect pre-sales to start soon, mobile mapping systems to ship within the first half of the year and data products to become available momentarily.

Our team works with vehicle owners, fleet operators and mobility providers who install the stereo sensors and contribute by expanding our global map during their everyday operations. Fleet partners are economically incentivized or desire to advance their own autonomy or data analytics products. The project in Berlin for example is backed by Bombardier, Siemens and Alba, who have a strategic interest in the map.

On the other hand, we are working with automotive suppliers and OEMs on autonomy projects leveraging our Visual Inertial Navigation System, which references the map in the cloud.

T.: How much impact will these results have on potential political decisions?

C.B.: The applications of our disruptively scalable maps potentially reach far beyond automotive. Cities and local authorities for example show increasing interest: As we build the digital infrastructure for autonomous vehicles, the same information can be used by smart cities to reduce traffic congestion, prevent accidents or plan maintenance work.